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Dictionary Learning

Dictionary Learning is an important problem in multiple areas, ranging from computational neuroscience, machine learning, to computer vision and image processing. The general goal is to find a good basis for given data. More formally, in the Dictionary Learning problem, also known as sparse coding, we are given samples of a random vector $y\in\mathbb{R}^n$, of the form $y=Ax$ where $A$ is some unknown matrix in $\mathbb{R}^{n×m}$, called dictionary, and $x$ is sampled from an unknown distribution over sparse vectors. The goal is to approximately recover the dictionary $A$.

Source: Polynomial-time tensor decompositions with sum-of-squares

Papers

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Showing 451–500 of 823 papers

TitleStatusHype
Dictionary Learning by Dynamical Neural Networks—0
Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories—0
Dictionary Learning and Sparse Coding on Statistical Manifolds—0
Structured Analysis Dictionary Learning for Image ClassificationCode0
Compressed Dictionary Learning—0
On Learning Sparsely Used Dictionaries from Incomplete Samples—0
Towards Learning Sparsely Used Dictionaries with Arbitrary Supports—0
Multi-focus Image Fusion using dictionary learning and Low-Rank RepresentationCode0
Dictionary learning -- from local towards global and adaptive—0
Learning Simple Thresholded Features with Sparse Support Recovery—0
Binary Matrix Factorization via Dictionary Learning—0
White matter fiber analysis using kernel dictionary learning and sparsity priors—0
Cross-Domain Visual Recognition via Domain Adaptive Dictionary Learning—0
Multimodal Sparse Bayesian Dictionary Learning—0
Representation Learning and Recovery in the ReLU Model—0
Deep Dictionary Learning: A PARametric NETwork Approach—0
Unsupervised Band Selection of Hyperspectral Images via Multi-dictionary Sparse Representation—0
Convolutional Analysis Operator Learning: Acceleration and ConvergenceCode0
Information Assisted Dictionary Learning for fMRI data analysisCode0
Weakly-supervised Dictionary Learning—0
Analysis of Fast Alternating Minimization for Structured Dictionary Learning—0
Learning Light Field Reconstruction from a Single Coded Image—0
Robust Kronecker Component Analysis—0
Denoising Dictionary Learning Against Adversarial Perturbations—0
Frame-based Sparse Analysis and Synthesis Signal Representations and Parseval K-SVD—0
Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free ApproachCode0
Demystifying overcomplete nonlinear auto-encoders: fast SGD convergence towards sparse representation from random initialization—0
Travel time tomography with adaptive dictionaries—0
Image Super-resolution via Feature-augmented Random ForestCode0
Low-dose spectral CT reconstruction using L0 image gradient and tensor dictionary—0
Learning Based Segmentation of CT Brain Images: Application to Post-Operative Hydrocephalic Scans—0
Noise Level Estimation for Overcomplete Dictionary Learning Based on Tight Asymptotic Bounds—0
Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification—0
OnACID: Online Analysis of Calcium Imaging Data in Real Time—0
Alternating minimization for dictionary learning with random initialization—0
Denoising Gravitational Waves using Deep Learning with Recurrent Denoising Autoencoders—0
STARK: Structured Dictionary Learning Through Rank-one Tensor Recovery—0
Alternating minimization for dictionary learning: Local Convergence Guarantees—0
Concave losses for robust dictionary learning—0
Robust Photometric Stereo via Dictionary Learning—0
Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics—0
Deep Self-taught Learning for Remote Sensing Image Classification—0
Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer—0
VIDOSAT: High-dimensional Sparsifying Transform Learning for Online Video DenoisingCode0
Learning Discriminative Latent Attributes for Zero-Shot Classification—0
Learning Discriminative ab-Divergences for Positive Definite Matrices—0
Robust Surface Reconstruction from Gradients via Adaptive Dictionary Regularization—0
Robust Photometric Stereo Using Learned Image and Gradient Dictionaries—0
Multimodal Image Super-resolution via Joint Sparse Representations induced by Coupled DictionariesCode0
Learning quadrangulated patches for 3D shape parameterization and completion—0
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